---
title: "Resources"
output: rmarkdown::html_document
vignette: >
%\VignetteIndexEntry{resources}
%\VignetteEngine{knitr::rmarkdown}
%\VignetteEncoding{UTF-8}
---
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
```
# Resources
## Article tutorials
- **Multiple Methods for Visualizing Human Language: A Tutorial for Social and Behavioural Scientists**
[OSF preprint](https://osf.io/preprints/psyarxiv/nxfvr_v1)
- **The *text* package tutorial**
[Full text on PsycNET](https://doi.org/10.1037/met0000542).
[OSF preprint](https://osf.io/preprints/psyarxiv/293kt_v1).
[Tutorial code](https://r-text.org/articles/psychological_methods.html)
- **The Language-Based Assessment Model (L-BAM) Library**
[OSF preprint](https://osf.io/preprints/psyarxiv/n8rza_v1)
[Tutorial code](https://r-text.org/articles/lbam_tutorial.html)
## Selected published articles advancing the *text* package
- Nilsson, A. H., Runge, J. M., Ganesan, A. V., Lövenstierne, C. V. N., Soni, N., & Kjell, O. N. (2025).
*Automatic implicit motive codings are at least as accurate as humans’ and 99% faster.*
*Journal of Personality and Social Psychology.*
[Article link](https://doi.org/10.1037/pspp0000544)
- Gu, Z., Kjell, K., Schwartz, H. A., & Kjell, O. (2025).
*Natural language response formats for assessing depression and worry with large language models: A sequential evaluation with model pre-registration.*
*Assessment, 10731911251364022.*
[Article link](https://journals.sagepub.com/doi/full/10.1177/10731911251364022)
- Nilsson, A. H., Eichstaedt, J. C., Lomas, T., Schwartz, A., & Kjell, O. (2024).
*The Cantril Ladder elicits thoughts about power and wealth.*
*Scientific Reports, 14(1), 2642.*
[Article link](https://www.nature.com/articles/s41598-024-52939-y)
## Blog posts and tutorials
- [**Implicit Motives Tutorial**](https://r-text.org/articles/implicit_motives_tutorial.html)
- [**Installing and Managing Python Environments with `reticulate`**](https://r-text.org/articles/reticulate.html)
- [**Creating a Singularity Container to Run HuggingFace Transformers Models in R**](https://r-text.org/articles/singularity_transformers_container.html)
- [**How to Best Manage Computationally Heavy Analyses**](https://r-text.org/articles/)
- [**HuggingFace Language Models Are Downloaded in `.cache`**](https://r-text.org/articles/removing_huggingface_transformers_cache_files.html)
- [**HuggingFace Transformers in R: Word Embeddings Defaults and Specifications**](https://r-text.org/articles/text.html)
- [**Pre-registration and Researcher Degrees of Freedom**](https://r-text.org/articles/pre_registration_and_transformers.html)